This moves the different canonicalizations of regions into one place and invokes them in the fixed-point iteration of the canonicalizer.

PiperOrigin-RevId: 281617072

PiperOrigin-RevId: 281605471

If the sizes are specified as arguments to the subview op, then the
shape must be dynamic as well.

PiperOrigin-RevId: 281591608

PiperOrigin-RevId: 281580028

This is a simple multi-level DCE pass that operates pretty generically on
the IR. Its key feature compared to the existing peephole dead op folding
that happens during canonicalization is being able to delete recursively
dead cycles of the use-def graph, including block arguments.

PiperOrigin-RevId: 281568202

The current SubViewOp specification allows for either all offsets,
shape and stride to be dynamic or all of them to be static. There are
opportunities for more fine-grained canonicalization based on which of
these are static. For example, if the sizes are static, the result
memref is of static shape. The specification of SubViewOp is modified
to allow on or more of offsets, shapes and strides to be statically
specified. The verification is updated to ensure that the result type
of the subview op is consistent with which of these are static and
which are dynamic.

PiperOrigin-RevId: 281560457

This CL uses the pattern rewrite infrastructure to implement a simple VectorOps -> VectorOps legalization strategy to unroll coarse-grained vector operations into finer grained ones.
The transformation is written using local pattern rewrites to allow composition with other rewrites. It proceeds by iteratively introducing fake cast ops and cleaning canonicalizing or lowering them away where appropriate.

This is an example of writing transformations as compositions of local pattern rewrites that should enable us to make them significantly more declarative.

PiperOrigin-RevId: 281555100

This interface provides more fine-grained hooks into the AsmPrinter than the dialect interface, allowing for operations to define the asm name to use for results directly on the operations themselves. The hook is also expanded to enable defining named result "groups". Get a special name to use when printing the results of this operation.
The given callback is invoked with a specific result value that starts a
result "pack", and the name to give this result pack. To signal that a
result pack should use the default naming scheme, a None can be passed
in instead of the name.

For example, if you have an operation that has four results and you want
to split these into three distinct groups you could do the following:

  setNameFn(getResult(0), "first_result");
  setNameFn(getResult(1), "middle_results");
  setNameFn(getResult(3), ""); // use the default numbering.

This would print the operation as follows:

  %first_result, %middle_results:2, %0 = "my.op" ...

PiperOrigin-RevId: 281546873

This operator is used for internal debugging purposes.

PiperOrigin-RevId: 281544152

PiperOrigin-RevId: 281506693

PiperOrigin-RevId: 281501234

PiperOrigin-RevId: 281483447

Closes tensorflow/mlir#246

PiperOrigin-RevId: 281442685

Fix registered size of indirect MemRefType kernel arguments.

PiperOrigin-RevId: 281362940

The `vector.strided_slice` takes an n-D vector, k-D `offsets` integer array attribute, a
k-D `sizes` integer array attribute, a k-D `strides` integer array attribute and extracts
the n-D subvector at the proper offset.

Returns an n-D vector where the first k-D dimensions match the `sizes` attribute.
The returned subvector contains the elements starting at offset `offsets` and ending at
`offsets + sizes`.

Example:
```
  %1 = vector.strided_slice %0
      {offsets : [0, 2], sizes : [2, 4], strides : [1, 1]}:
    vector<4x8x16xf32> // returns a vector<2x4x16xf32>
```

This op will be useful for progressive lowering within the VectorOp dialect.

PiperOrigin-RevId: 281352749

In the particular case where the size of a memref dimension is 1, double printing would happen because printLast was called unconditionally.
This CL fixes the print and updates an incorrect test that should have caught this in the first place.

PiperOrigin-RevId: 281345142

PiperOrigin-RevId: 281338738

PiperOrigin-RevId: 281338448

This method is needed for N->1 conversion patterns to retrieve remapped
Values used in the original N operations.

Closes tensorflow/mlir#237

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/237 from dcaballe:dcaballe/getRemappedValue 1f64fadcf2b203f7b336ff0c5838b116ae3625db
PiperOrigin-RevId: 281321881

Closes tensorflow/mlir#245

PiperOrigin-RevId: 281321459

The command-line flag name `lower-to-llvm` for the pass performing dialect
conversion from the Standard dialect to the LLVM dialect is misleading and
inconsistent with most of the conversion passses. It leads the user to believe
that there are no restrictions on what can be converted, while in fact only a
subset of the Standard dialect can be converted (with operations from other
dialects converted by separate passes). Use `convert-std-to-llvm` that better
reflects what the pass does and is consistent with most other conversions.

PiperOrigin-RevId: 281238797

This commit add `dialect-attribute-entry` requirements on function arguments,
function results, and function attributes to the documentation.

PiperOrigin-RevId: 281227740

The toy language uses element-wise multiplication. Transposing and multiplying
two tensors with shape <2, 3> gives a tensor with shape <3, 2>.

Closes tensorflow/mlir#227

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/227 from ombre5733:toy-ch1-docu-fix d79e5d3f9e3d5150a7ac8aac28b899df5a0d10a0
PiperOrigin-RevId: 281221671

Iterates each element to build the array. This includes a little refactor to
combine bool/int/float into a function, since they are similar. The only
difference is calling different function in the end.

PiperOrigin-RevId: 281210288

Closes tensorflow/mlir#247

PiperOrigin-RevId: 281185661

PiperOrigin-RevId: 281169885

Closes tensorflow/mlir#243

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/243 from bondhugula:patch-2 fb682996efde001189414a4c7aa59ce42ace7831
PiperOrigin-RevId: 281167834

Adds unit tests for subview offset and stride argument constant folding.

PiperOrigin-RevId: 281161041

The variant that accepts a type will check that the parsed attribute is a valid instance of AttrType. The non-type variant would silently fail in this case, leading to garbage attribute values.

PiperOrigin-RevId: 281136528

PiperOrigin-RevId: 281131561

Convert chained `spirv::BitcastOp` operations into
one `spirv::BitcastOp` operation.

Closes tensorflow/mlir#238

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/238 from denis0x0D:sandbox/canon_bitcast 4352ed4f81b959ec92f849c599e733b62a99c010
PiperOrigin-RevId: 281129234

PiperOrigin-RevId: 281114034

The assertion was introduced in the early days of dialect conversion
infrastructure when we had the matching function separate from the rewriting
function. The infrastructure evolved to have a common matchAndRewrite function
and the separate matching function was dropped without chaning the rewriting
that became matchAndRewrite. This has led to assertion being triggered. Return
a matchFailure instead of failing an assertion on unsupported types.

Closes tensorflow/mlir#230

PiperOrigin-RevId: 281113741

This CL utilizies the more robust fusion feasibility analysis being built out in LoopFusionUtils, which will eventually be used to replace the current affine loop fusion pass.

PiperOrigin-RevId: 281112340

This improves consistency and will concretely avoid collisions between VectorExtractElementOp and ExtractElementOp when they are included in the same transforms / rewrites.

PiperOrigin-RevId: 281101588

PiperOrigin-RevId: 281042016

This makes the flags consistent with the naming scheme used elsewhere in the
codebase for dialect conversions.

PiperOrigin-RevId: 281027517

PiperOrigin-RevId: 280888290

This commit fixes several attribute dict syntax errors in the documentation.

PiperOrigin-RevId: 280726269

This CL added op definitions for a few bit operations:

* OpBitFieldInsert
* OpBitFieldSExtract
* OpBitFieldUExtract

Closes tensorflow/mlir#233

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/233 from denis0x0D:sandbox/bit_field_ops e7fd85b00d72d483d7992dc42b9cc4d673903455
PiperOrigin-RevId: 280691816